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Loss Landscape created with data from the training process of a convolutional network that uses dropout. The use of dropout produces this distinctive morphology and sharp patterns during the training process. Imaginette Dataset. SGD-Adam. Bs=16, bn, lr-sched, train mode, log scaled.

This piece has been created through a multi day process composed of different stages that begin with the training of deep learning neural networks and proceeds through a number of phases until arriving to the final artwork.

Created by Javier Ideami.
For more about the Loss Landscape project visit https://losslandscape.com

Explorer of A.I, AR, advanced visualizations & others, multidisciplinary engineer & creative director. As a multidisciplinary creative director, engineer, artist and entrepreneur, Javier has travelled the world leading projects, exhibiting his work and giving talks, from Silicon Valley to the jungles of Bali, from Stanford University, through the United Nations FAO HQ and the financial center of London, to the International Cultural Diplomacy Conference in Berlin and many others. In his latest works, Javier Ideami produces A.I artworks through a complex process that can last many days. The process begins with training a neural network and capturing relevant data. This multidimensional data is then transformed into a 3D piece which is...